A Guide to Teaching Statistics - Innovations and Best Practices

Series Editors’ Preface

Preface

I Course Preparation

Chapter 1 Teaching Statistics A beginning

So Why Teach Statistics?

Historical Pedagogical Controversies

Who should teach statistics?

Statistics labs and related technology

Content of statistics courses

Statistics in Relation to the Discipline

Sequence of the Class and Topics

Introducing Research Methods within the Context of Statistics

Student Populations

Mathematical ability

Cognitive ability and learning styles

Self-efficacy and motivation

Gender

Helping Your Students Survive Statistics

Conclusion

Chapter 2 Nuts and Bolts of Teaching Statistics

Syllabus Construction

Textbook Selection

Conceptual orientation

Level of difficulty

Chapter topics and organization

Core formulas and vocabulary

Type of data sets/quality of the exercises

Traditional Versus Electronic Textbooks

Supplemental Materials

Study guides

Companion Web sites

Computer tutorials

Electronic Discussion Boards

Multimedia Tools

Presentation technology

Interactive applications: Java applets, Flash, Shockwave, and HTML

Multimedia simulation programs

Conclusion

II Theoretical and Pedagogical Concerns

Chapter 3 Educational Reform in Statistics

Educational Reform

Statistically Educated Students

Statistical Literacy

Knowledge elements

Dispositional elements

Statistical Thinking

Statistical Reasoning

Misconceptions Impacting the Development of Literacy, Thinking, and Reasoning

Final Thoughts on Statistical Literacy, Thinking, and Reasoning

Assessment

What is the role of assessment?

What is the role of authentic assessment?

Assessment and learning outcomes or goals

Conclusion

Chapter 4 In the Classroom

Conceptual Learning, Active Learning, and Real Data

Conceptual learning versus rote memorization

Active learning

Real data

Instructional Techniques

Lecture

The use of questions

Practice problems and examples

Journal assignments

Activities and demonstrations

Writing assignments

Concept maps

Cooperative learning

Projects

Assessment

Principles of effective assessment

Mastery learning

Confronting Fear and Anxiety

Conclusion

III Teaching Specific Statistical Concepts

Chapter 5 Descriptive Statistics and Bivariate Distributions

Graphing Data

The use of graphs in science

Elements of good design

Human graphical perception

Available graphing methods

Software design

Normal Distribution

Measures of Central Tendency

Measures of Variability

Correlation

Simple Linear Regression

Computer Applications

Conclusion

Chapter 6 Teaching Hypothesis Testing

Samples, Sampling Distributions, and the Central Limit Theorem

Confidence Intervals

Introduction to Null Hypothesis Testing

Additional Introduction to Hypothesis Testing Concepts

Power

Effect sizes

Type I and Type II errors

Analysis of Variance

Introduction to ANOVA

Violating ANOVA assumptions

Factorial ANOVA

General linear model

The Debate Surrounding Null Hypothesis Significance Testing

Nonparametric Statistics

Computer Applications

Conclusion

IV Advanced Topics and Approaches

Chapter 7 Data Analysis in Statistical Education

Teaching with Statistical Software Tools

Data Analysis Packages

SPSS

Microsoft Excel

Other commercial data analysis programs

Comparing data analysis programs

Data Analysis Software Textbooks

Using Data Sets in the Classroom

Artificial data sets for the classroom

Reality-based data sets

Finding appropriate reality-based data sets

Drawbacks to using real data sets

Conclusion

Chapter 8 Endings and Beginnings

Multivariate Statistics

Multiple regression

Logistic regression

Additional multivariate techniques

Special Topics

Ethics

Diversity

Online Statistical Education

Finishing up Any Statistics Course

Final Thoughts

References

Index